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Comparison · Analytics
dplyr vs silx
A side-by-side editorial comparison of dplyr and silx — release velocity, themes, recent moves, and the top alternatives to consider.
dplyr vs silx: at a glance
What is dplyr?
After two quiet years dplyr widened its verb vocabulary in one release
dplyr sat on patch releases from late 2023 until 1.2.0 landed in February 2026, and that release did a lot at once: a filter_out() counterpart to filter(), elementwise when_any() and when_all(), and three new recoding verbs alongside case_when(). It also rewrote if_else(), case_when() and coalesce() in C via vctrs, and promoted .by and reframe() from experimental to stable. The follow-up 1.2.1 is a compliance patch.
What is silx?
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
silx releases a couple of times a year and reached 3.0.0 in April 2026, which raised the Python floor to 3.10 and switched the default Qt binding to PySide6. The same release reworked the viewer's data views: 3D scatter support, dedicated RGB(A) image views, the composite ImageView split into Plot2dView and ComplexImageView, and NXdata stacks displayed as images. 3.1.0 has since added asinh axis scaling, the twilight colormaps, and dark-theme icons.
dplyr vs silx: editorial side-by-side
dplyr
0.0ANALYTICS
After two quiet years dplyr widened its verb vocabulary in one release
◆ Current state
dplyr sat on patch releases from late 2023 until 1.2.0 landed in February 2026, and that release did a lot at once: a filter_out() counterpart to filter(), elementwise when_any() and when_all(), and three new recoding verbs alongside case_when(). It also rewrote if_else(), case_when() and coalesce() in C via vctrs, and promoted .by and reframe() from experimental to stable. The follow-up 1.2.1 is a compliance patch.
◆ Where it's heading
The package is expanding its verb set deliberately, through published Tidyup design proposals rather than ad-hoc additions, and each new verb targets a case where the old idiom was error-prone - most obviously NA handling in negated filters. Underneath, hot paths keep moving from R into C, so the API grows while the runtime cost falls.
◆ Prediction
Expect the remaining experimental surface to follow .by and reframe() toward stable, and further hot paths to be rewritten in C via vctrs. The two Tidyup proposals referenced here suggest more of the filter and recode families is still being designed.
silx
2.5ANALYTICS
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
◆ Current state
silx releases a couple of times a year and reached 3.0.0 in April 2026, which raised the Python floor to 3.10 and switched the default Qt binding to PySide6. The same release reworked the viewer's data views: 3D scatter support, dedicated RGB(A) image views, the composite ImageView split into Plot2dView and ComplexImageView, and NXdata stacks displayed as images. 3.1.0 has since added asinh axis scaling, the twilight colormaps, and dark-theme icons.
◆ Where it's heading
The project is doing a generational refresh of its GUI layer: modern Qt binding, modules broken out of the composite widgets that had accumulated responsibilities, and the theming work that a desktop application needs to look current. Underneath, the recurring fixes are about HDF5 behavior in real facility environments — file locking, NFS refresh, Windows display paths — which is where a synchrotron toolkit actually gets stressed. Feature growth is concentrated in silx view rather than the library API.
◆ Prediction
Expect the 3.1.x line to keep filling in plotting options and theming, with the PySide6 default flushing out binding-specific bugs from downstream applications over the next few releases.
Alternatives to dplyr and silx
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either dplyr or silx.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
statsmodels
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
StatsBase.jl
StatsBase.jl is in caretaker mode — correctness fixes in, dependency bumps out.
iris
Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.
shiny
Shiny made reactive apps observable, then gave them a way to tear themselves down
Recent activity from dplyr and silx
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2d agosilx3.1.0: asinh axis scaling, twilight colormaps, dark-theme icons
- 3mo agosilx3.0.1: 2026/05/07
- 3mo agosilx3.0.0: PySide6 becomes the default Qt binding, Python 3.10 required ⚡
- 3mo agosilx3.0.0rc1: release candidate for the PySide6 migration
- 4mo agodplyrFull compliance with the R C API
- 6mo agodplyrfilter_out(), when_any() and three recoding verbs land in 1.2.0 ⚡
- 1y agosilx2.2.2: 2025/04/07
- 1y agosilx2.2.0b0: HSDS URL support and a multi-curve comparison window
- 2y agodplyrNamespaced join_by() helpers and refreshed bundled datasets
- 2y agodplyrDeprecation message and setequal() consistency fixes
- 3y agodplyrAll-NA join key fix and count() documentation
- 3y agodplyrJoins gain a relationship argument and warn far less often
Frequently asked questions
What is the difference between dplyr and silx?
They serve adjacent needs but don't currently overlap on shipped themes. silx is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is dplyr better than silx?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. silx is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to dplyr?
Top dplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dplyr alternatives" section above for the current picks, or visit /alternatives/dplyr for the full list with editorial commentary on each.
What are the best alternatives to silx?
Top silx alternatives in Analytics are ranked by recent ship velocity. Browse the "silx alternatives" section above for the current picks, or visit /alternatives/silx for the full list with editorial commentary on each.